Assessing the stability of Pd-exchanged sites in zeolites with the aid of a high throughput quantum chemistry workflow

被引:8
作者
Aljama, Hassan A. [1 ]
Head-Gordon, Martin [2 ,3 ]
Bell, Alexis T. [1 ]
机构
[1] Univ Calif Berkeley, Dept Chem & Biomol Engn, Berkeley, CA 94720 USA
[2] Univ Calif Berkeley, Dept Chem, Berkeley, CA 94720 USA
[3] Lawrence Berkeley Natl Lab, Div Chem Sci, Berkeley, CA 94720 USA
关键词
DENSITY-FUNCTIONAL THEORY; PASSIVE NOX; ADSORPTION THERMODYNAMICS; QM/MM SIMULATIONS; BETA-ZEOLITE; ETHYLENE; AL; DEHYDROGENATION; DISPERSION; LOCATION;
D O I
10.1038/s41467-022-29505-z
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Cation exchanged-zeolites are functional materials with a wide range of applications from catalysis to sorbents. They present a challenge for computational studies using density functional theory due to the numerous possible active sites. From Al configuration, to placement of extra framework cation(s), to potentially different oxidation states of the cation, accounting for all these possibilities is not trivial. To make the number of calculations more tractable, most studies focus on a few active sites. We attempt to go beyond these limitations by implementing a workflow for a high throughput screening, designed to systematize the problem and exhaustively search for feasible active sites. We use Pd-exchanged CHA and BEA to illustrate the approach. After conducting thousands of explicit DFT calculations, we identify the sites most favorable for the Pd cation and discuss the results in detail. The high throughput screening identifies many energetically favorable sites that are non-trivial. Lastly, we employ these results to examine NO adsorption in Pd-exchanged CHA, which is a promising passive NOx adsorbent (PNA) during the cold start of automobiles. The results shed light on critical active sites for NOx capture that were not previously studied. The identification of active sites in cation exchanged-zeolites is computationally highly demanding. Here the authors employ a DFT-based computational framework to identify the energetically most favorable adsorption sites in any zeolite using a systematic high-throughput approach.
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页数:9
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